Some signal transmitters for cellular communications utilize QAM (quadrature amplitude modulation) to increase the number of signals that can be transmitted on a given channel. QAM is a method of combining two amplitude-modulated (AM) signals into a single channel to effectively double the effective bandwidth. QAM is used with pulse amplitude modulation (PAM) in digital systems, especially in wireless applications.
In a QAM (quadrature amplitude modulation) signal, there are two carriers, each having the same frequency but differing in phase by 90 degrees (one quarter of a cycle, from which the term quadrature arises). The two modulated carriers are combined at the source for transmission. At the destination, the carriers are separated, the data is extracted from each, and then the data is combined into the original modulating information.
Radio transmitters amplify input signals. It is desired that the gain of such transmitters be linear for the entire range of input signals. Contemporary baseband techniques for linearization of radio transmitters, and in particular of power amplifiers, rely on frequent estimation of the nonlinear transmitter gain in terms of a single-argument complex gain function of the input signal, which after inversion is used for its preamplification or predistortion. The cascade of the nonlinear transmitter with the predistortion gain has the properties of a linearized system with residual distortions depending on the accuracy of initial gain estimation. Change of the average transmitter gain over time, which can be caused by different ambient factors, may significantly reduce the accuracy of gain estimation especially in cases when the predistortion process has different settling time constants over dynamic range. Therefore, the bandwidth of the adaptation process is increased from zero to a sufficient minimum providing reasonable convergence and tracking speeds for the fastest gain changes as well as suppression of white noise. A problem arises when in addition to the systematic gain changes there are system impairments in the same bandwidth causing random variations of the signal magnitude or phase, where the latter could be the result of phase noise or modulation/demodulation frequency instability.
Some of the major disadvantages of current systems are dependency on test signals or specific signaling formats for identification of such system impairments, as well as the complexity of the solutions requiring powerful offline processing capabilities. In one example signal transmission is attempted with minimal distortions such as bias, lock and quadrature angle errors by means of adaptive signal predistortion prior to transmission. Linearization of the transmitter is achieved by a separate predistortion block called ‘predistorter with memory’ which affects the transmitted signal before the previously mentioned adaptive predistortion. Although exploiting the idea of two separate predistortion blocks—one for compensation of transmitter nonlinearity and another for the rest of the system impairments (most of which are of linear nature), the solution lacks generality due to the use of designated test sequences for nonlinearity estimation and constellation models for impairment identification. Moreover, the level of complexity of the suggested identification and compensation procedures poses serious questions about the efficiency of its implementation.
Another technique attempts to estimate amplifier nonlinearity with limited sensitivity to IF noise and phase noise. Invariance with respect to system impairments is achieved by functional modeling of amplifiers utilizing spline approximation of noisy measurement data. A major drawback of the proposed system is that the measurements are conducted by stimulating the amplifier with designated reference bi-tone signals. In addition, there is a fair amount of computational complexity involved in the approximation process.
Yet another approach is based on a technique of inverse adaptive control, which includes a two-step process of linearization and impairment compensation. First, a forward polynomial model of the amplifier is created applying adaptive system identification techniques. Second, the forward model is used to generate noiseless signals applied as reference inputs to an inverse polynomial model of the amplifier. The parameters of a look-up-table based predistortion gain block implementing the real-time linearization are derived after format conversion from the inverse amplifier model. By its nature, this method is similar to the spline approximation technique. Implementation of polynomial nonlinearity estimation involves computationally expensive operations like raising signal samples to a power larger than 2 as well as a multi-step derivation of the corresponding inverse polynomials performing the predistortion.
Extensive analysis of multi-channel impairments in radio transmitters (i.e. impairments related to the way more than one input signals of the transmitter are combined into a single one prior to transmission) employing QAM has been performed along with the research of direct conversion techniques and predistorters for linearization of memoryless RF power amplifiers. As a result, symmetric and non-symmetric matrix models of gain and phase imbalance as well as DC level bias originating in the quadrature modulator sections of these transmitters have been developed.
Accordingly, optimal methods for compensation of quadrature modulator error factors in the transmitted waveforms have been designed using inverse models of the impairment matrices to predistort the transmitted signals prior to quadrature modulation. From application perspective, two types of compensation techniques have been demonstrated: (1) ones using special calibration sequences that are executed before a transmission session, and (2) ones providing continuous optimization of the compensation parameters during normal transmission.
Notwithstanding their complexity, performance or efficiency, the existing solutions demonstrate the common disadvantage of being restricted to particular devices in the transmitter chain, such as quadrature modulator sections, that cause a particular type of gain imbalance, crosstalk or DC level bias. In addition to the major assumption for memoryless transmitter nonlinearity and multi-channel impairments, hypotheses are made about the (1) linearity, (2) symmetry, and (3) location of the impairments. Interestingly, although being intended to operate in systems for predistortion linearization of RF power amplifiers the matrix inversion algorithms have been designed to utilize independent processing and correction elements from the ones implementing the linearization.
A number of existing solutions to the problem of multi-channel impairment compensation in signal transmitters are aimed at improving the overall quality of transmission by perfecting the worst performing functional blocks in the transmitter chain. For example, these are the quadrature modulator stages in radio transmitters employing quadrature amplitude modulation. The proposed systems can be separated in two corresponding groups depending on whether the performance of the targeted functional block is calibrated before or continuously improved during normal transmitter operation.
Calibration algorithms for minimization of quadrature modulator errors such as gain/phase imbalance and carrier leakage causing DC level bias involve determination of predistortion parameters for a quadrature modulator, quadrature measurement and calibration of a vector modulator, and calibration of vector modulators using a scalar detectors. A technique for adjusting the balance and the 90-deg phase difference of the outputs of a quadrature modulator has also been used. A system architecture allowing continuous optimization of gain and phase imbalance during transmission involves a quadrature modulator imbalance estimator and modulator stage using it. A technique for adaptive compensation of carrier leakage in a quadrature modulator involves a quadrature modulator with set-and-forget carrier leakage compensation.
A common disadvantage of the above-cited solutions is the lack of generality in the treatment of transmit channel impairments, which are often limited to a single functional block of the transmitter chain and assumed to be linear in nature. In addition, the cause of channel crosstalk is attributed only to loss of orthogonality between the quadrature phases and is represented by antipodal terms that are equal in magnitude and opposite in sign (i.e. demonstrating a certain level of symmetry). The suggested calibration or adaptive procedures are explicitly designed to improve the performance of two-channel transmitters and, thus, their upgrade for multi-channel transmitters is not straightforward. Moreover, application of these techniques in a system for transmitter linearization would require a significant amount of extra computational or hardware resources to be dedicated for channel imbalance compensation because of the high degree of incompatibility between the existing hardware-efficient linearization algorithms and the quadrature modulator algorithms.